Deep Learning for Artificial Intelligence

Master Course at Universitat Politècnica de Catalunya (Autumn 2017)

Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of large-scale annotated datasets and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which were previously addressed with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks or Q-nets for reinforcement learning have shaped a brand new scenario in signal processing.

This course will cover the basic principles of deep learning from both an algorithmic and computational perspectives.  Complete learning systems in different Deep Learning frameworks and platforms will be introduced via hadns-on, projects and assignments. You will learn to solve new classes of problems that were once thought prohibitively challenging, and come to better appreciate the complex nature of human intelligence as you solve these same problems effortlessly using deep learning methods.

We have developed this course with other professors at UPC from different research groups. We hope that you enjoy its content!

 

Practical details

My contribution: Supercomputing platforms and middleware for DL

Lin to the part of DLAI course that will cover the basic principles of deep learning from computational perspective

Registration

Registration procedure depends on the student profile:

  • Master students at ETSETB and FIB: Follow the regular schedule from your academic office.
  • Mobility students: If your host institution has signed an agreement with UPC ETSETB Telecom BCN school, you can request a mobility from your host institution and sign up for the course under the same conditions as ETSETB students.
  • Students at UPC but not in ETSETB: Contact the your academic office and request being allowed to take this course. If accepted, contact ETSETB academic office and request more details.
  • Non UPC nor mobility students: You must apply for being accepted in the course and cover the 100% cost of the ECTS credits, without the support of the public funds. This corresponds to 143,08 € per ECTS credit (Summer 2016). If you are interested in this option, please contact the ETSETB Telecom BCN academic office, with an e-mail to secretaria@etsetb.upc.edu or calling at 93 405 4174 / 93 401 6772 / 93 401 5966 or 93 401 6750 in the morning (Monday to Thursday from 11 to 14 and Fridays from 11 to 13) or noons (Wednesdays and Thursdays from 16 to 17h).

My contribution

Link the part of DLAI course that will cover the basic principles of deep learning from computational perspective

More information

More information about the course can be found in the following  links:

 

 

2017-09-25T12:26:48+00:00 July 7th, 2017|